Auto-tuning TRSM with an asynchronous task assignment model on multicore, multi-GPU and coprocessor systems

Clícia Pinto, Marcos E. Barreto, M. Boratto
{"title":"Auto-tuning TRSM with an asynchronous task assignment model on multicore, multi-GPU and coprocessor systems","authors":"Clícia Pinto, Marcos E. Barreto, M. Boratto","doi":"10.1109/AICCSA.2016.7945637","DOIUrl":null,"url":null,"abstract":"The increasing need for computing power today justifies the continuous search for techniques that decrease the time to answer usual computational problems. To take advantage of new hybrid parallel architectures composed by multithreading and multiprocessor hardware, our current efforts involve the design and validation of highly parallel algorithms that efficently explore the characteristics of such architectures. In this paper, we propose an automatic tuning methodology to easily exploit multicore, multi-GPU and coprocessor systems. We present an optimization of an algorithm for solving triangular systems (TRSM), based on block decomposition and asynchronous task assignment, and discuss some results.","PeriodicalId":448329,"journal":{"name":"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2016.7945637","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The increasing need for computing power today justifies the continuous search for techniques that decrease the time to answer usual computational problems. To take advantage of new hybrid parallel architectures composed by multithreading and multiprocessor hardware, our current efforts involve the design and validation of highly parallel algorithms that efficently explore the characteristics of such architectures. In this paper, we propose an automatic tuning methodology to easily exploit multicore, multi-GPU and coprocessor systems. We present an optimization of an algorithm for solving triangular systems (TRSM), based on block decomposition and asynchronous task assignment, and discuss some results.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于多核、多gpu和协处理器系统的异步任务分配模型的自动调优TRSM
当今对计算能力日益增长的需求证明了不断寻找能够减少回答通常计算问题所需时间的技术是正确的。为了利用由多线程和多处理器硬件组成的新型混合并行架构,我们目前的工作涉及设计和验证高度并行的算法,以有效地探索这种架构的特征。在本文中,我们提出了一种自动调优方法,以方便地利用多核,多gpu和协处理器系统。提出了一种基于分块分解和异步任务分配的三角系统(TRSM)求解算法的优化,并讨论了一些结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Foreword — Message from the general chairs Towards a framework for customer emotion detection Development of a thematic and structural elements grid for e-government strategies: Case study of Swiss cantons Complementary features for traffic sign detection and recognition Priority-MAC: A priority based medium access control solution with QoS for WSN
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1